RT Journal Article
SR Electronic
T1 LeafCutter: annotation-free quantification of RNA splicing
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 044107
DO 10.1101/044107
A1 Yang I Li
A1 David A Knowles
A1 Jack Humphrey
A1 Alvaro N. Barbeira
A1 Scott P. Dickinson
A1 Hae Kyung Im
A1 Jonathan K Pritchard
YR 2017
UL http://biorxiv.org/content/early/2017/09/07/044107.abstract
AB The excision of introns from pre-mRNA is an essential step in mRNA processing. We developed LeafCutter to study sample and population variation in intron splicing. LeafCutter identifies variable intron splicing events from short-read RNA-seq data and finds alternative splicing events of high complexity. Our approach obviates the need for transcript annotations and circumvents the challenges in estimating relative isoform or exon usage in complex splicing events. LeafCutter can be used both for detecting differential splicing between sample groups, and for mapping splicing quantitative trait loci (sQTLs). Compared to contemporary methods, we find 1.4–2.1 times more sQTLs, many of which help us ascribe molecular effects to disease-associated variants. Strikingly, transcriptome-wide associations between LeafCutter intron quantifications and 40 complex traits increased the number of associated disease genes at 5% FDR by an average of 2.1-fold as compared to using gene expression levels alone. LeafCutter is fast, scalable, easy to use, and available at https://github.com/davidaknowles/leafcutter.